Hybrid Taguchi Based Grey Algorithm for Multi Objective Optimization of Gas Metal Arc Welded DP1000 Steel

Abstract

Euro-6 norms for reduction of CO 2 emissions and ECE-R66-01 regulation for safer passenger transportation became legislative obligations for bus builders. These two adaptations increase the weight of a bus as nearly 600kg which also increases the fuel consumption nearly 1.5-3%. Dual phase (DP) steels can compensate these increases by decreasing the thickness of the components. Because, ferrite provides the steel with good formability and martensite increases the hardness and ultimate tensile strength in DP steels. This study focused on the multi response hybrid optimization of gas metal arc welding (GMAW) of DP1000 steel to determine the optimal parametric combination which gives the maximum ultimate tensile strength (UTS, MPa) and joint efficiency (JE) under minimum heat input (Q, kj/mm). Nine experimental trials which is based on the orthogonal array suggested by Taguchi method was carried out to investigate objective functions for optimization in the experimental range of GMAW parameters such as voltage (U, volt), welding speed (V, mm/min) and wire feed rate (f, m/min). The Taguchi method continued with Grey Relational Analysis (GRA) to overcome the multiobjective optimization model. Finally, Analysis of variance (ANOVA) method has been used to determine the significance of the welding parameters on the responses of UTS, JE and Q. This shows flexible applicability of Taguchi based GRA to find out the effect of each GMAW process parameters onto individual responses.